AutoAct vs ChatDev
Side-by-side comparison of two AI agent tools
Short answer
- AutoAct has had no commit in 20 months; ChatDev is actively maintained (3 commits in the last 90 days).
- ChatDev is growing faster: +402 GitHub stars in the last 30 days vs +0 for AutoAct.
- Pick AutoAct for: aCL 2024 AutoAct: Automatic Agent Learning from Scratch for QA via Self-Planning. Pick ChatDev for: chatDev 2.0: Dev All through LLM-powered Multi-Agent Collaboration.
From GitHub data refreshed daily.
AutoActopen-source
[ACL 2024] AutoAct: Automatic Agent Learning from Scratch for QA via Self-Planning
ChatDevopen-source
ChatDev 2.0: Dev All through LLM-powered Multi-Agent Collaboration
Metrics
| AutoAct | ChatDev | |
|---|---|---|
| Stars | 239 | 34.4k |
| Star velocity /mo | 0.4736842105263158 | 401.8421052631579 |
| Commits (90d) | 0 | 3 |
| Releases (6m) | 0 | 0 |
| Overall score | 0.1440900567232822 | 0.432443435811532 |
Pros
- +Eliminates dependency on expensive closed-source models like GPT-4, making agent development more accessible and cost-effective
- +Automatically synthesizes planning trajectories without requiring human annotation or manual trajectory creation
- +Implements division-of-labor strategy with specialized sub-agents for improved task decomposition and completion
- +Zero-code configuration makes multi-agent systems accessible to non-technical users
- +Proven track record with strong community adoption (31,000+ GitHub stars)
- +Versatile platform capable of handling diverse scenarios from software development to research automation
Cons
- -Primarily focused on question answering tasks, which may limit applicability to other agent use cases
- -Requires an existing tool library to function effectively, adding setup complexity
- -Performance may vary significantly depending on the quality and capabilities of the underlying open-source language model used
- -Recently transitioned from 1.0 to 2.0, potentially introducing stability concerns during the migration period
- -Limited technical documentation available for the new 2.0 platform features
- -May be overly complex for simple automation tasks that don't require multi-agent coordination
Use Cases
- •Building cost-effective QA agents for organizations without access to expensive closed-source language models
- •Creating reproducible agent systems in research environments with limited annotated training data
- •Developing multi-agent systems that require automatic task decomposition and specialized sub-agent coordination
- •Automated software development with virtual teams of specialized AI agents (CEO, CTO, Programmer roles)
- •Complex research automation requiring coordination between multiple AI agents with different expertise
- •Data visualization and 3D generation projects that benefit from multi-agent workflow orchestration
FAQ
- Which is more popular, AutoAct or ChatDev?
- ChatDev has more GitHub stars (34,437 vs 239).
- Which is more actively developed, AutoAct or ChatDev?
- ChatDev had more commits in the last 90 days (3 vs 0).
- Should I use AutoAct or ChatDev?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.